IDO1 Activity Predicts Lung Toxicity in Patients with Unresectable Stage III NSCLC and Chemoradiotherapy

Objectives Indoleamine 2,3-dioxygenase 1 (IDO1) acts as the key rate-limiting enzyme that converts tryptophan (Trp) to kynurenine (Kyn). Its activity was primarily induced by interferon-γ (IFN-γ), which was reported to play a role in the development of acute radiation-induced pneumonitis. In this study, we aimed to investigate the correlation between IDO1 activity and radiation-induced lung toxicity (RILT) in stage III nonsmall cell lung cancer (NSCLC) patients who were treated with chemoradiotherapy (CRT). Materials and Methods Systemic IDO1 activity was reflected by Kyn : Trp ratio. Plasma levels of Kyn and Trp in 113 stage III NSCLC patients were measured by high-performance liquid chromatography (HPLC) before the initiation of radiotherapy. Dynamic change of IDO1 activity was followed in 23 patients before, during, and after radiotherapy. We also used RNA sequencing (RNA-seq) data from the Cancer Genome Atlas Program (TCGA) database and performed gene set enrichment analysis (GSEA) to explore how IDO1 was involved in the development of RILT. Results 9.7% (11/113) of the whole group developed G3+ (greater than or equal to Grade 3) RILT. Preradiation IDO1 activity was significantly higher in patients who developed G3 + RILT than in nonG3 + RILT patients. (P = 0.029, AUC = 0.70). Univariate and multivariate analyses showed that high IDO1 activity was independently associated with the risk of G3 + RILT (P = 0.034). A predictive model combining both IDO1 activity and FEV1 was established for severe RILT and displayed a moderate predictive value (AUC = 0.83, P < 0.001). The incidence of G3 + RILT was 2.6% (1/38) in patients with an IDO activity ≤0.069 and FEV1 > 59.4%, and 50.0% (6/12) in those with an IDO activity >0.069 and FEV1 ≤ 59.4%. Of 23 patients with dynamic tracking, the IDO1 activity of postradiation was significantly lower than midradiation (P = 0.021), though no significant differences among the three time points were observed (P = 0.070). Bioinformatic analysis using RNA-seq data from 1014 NSCLC patients revealed that IDO mainly functioned in the inflammatory response instead of the late fibrosis process in NSCLC patients. Conclusion High baseline IDO1 activity combined with unfavorable baseline FEV1 was predictive of severe RILT in unresectable stage III NSCLC patients. IDO1 might play a role in the acute inflammatory response. Finding effective interventions to alleviate RILT using IDO inhibitors is warranted in the future.

(P � 0.070). Bioinformatic analysis using RNA-seq data from 1014 NSCLC patients revealed that IDO mainly functioned in the infammatory response instead of the late fbrosis process in NSCLC patients. Conclusion. High baseline IDO1 activity combined with unfavorable baseline FEV1 was predictive of severe RILT in unresectable stage III NSCLC patients. IDO1 might play a role in the acute infammatory response. Finding efective interventions to alleviate RILT using IDO inhibitors is warranted in the future.

Introduction
Lung cancer is one of the most lethal cancer types in China, with 85% of the patients being nonsmall cell lung cancer (NSCLC) [1,2]. Defnitive chemoradiotherapy (CRT) with consolidated immunotherapy is the standard of care for unresectable stage NSCLC patients [3]. Toracic radiation therapy (RT) plays a pivotal role in treating NSCLC, whereas causing radiation-induced lung toxicity (RILT). With the symptoms of cough, dyspnea, fever, and fbrotic changes on computed tomography (CT), RILT can impair the lung function of patients, leading to respiratory failure and even treatment-related mortality [4,5]. G3+ (greater than or equal to Grade 3) RILT or severe RILT happens in about 10% of patients and has raised increasing attention due to its high lethality [6,7]. Tus, it is of great signifcance to predict RILT, particularly severe RILT, in advance of radiation. Despite emerging attempts to build predictive models, there is still no efective model available for RILT in clinical practice [6,[8][9][10][11].
Indoleamine 2,3-dioxygenase 1 (IDO1) is the key ratelimiting enzyme in the tryptophan (Trp) metabolic reaction, serving as the most active enzyme that converts the essential amino acid L-Trp into L-kynurenine (Kyn) [12]. IDO1 is highly and constitutively expressed in NSCLC patients and acts as an immune checkpoint induced by potent mediators such as interferon-c (IFN-c), transforming growth factor-β (TGF-β), and other proinfammatory signals in the tumor microenvironment [13][14][15][16]. A study performed in colorectal cancer cell lines and animal models has shown that IDO1 blockade protected the normal small intestinal epithelium from radiation toxicity and accelerated recovery from radiation-induced side efects [17]. Even though the mechanism was not specifcally depicted in the study, it is noted that a correlation might exist between IDO status and radiation-induced toxicity.
Tere has been limited study relating to IDO's role in the mechanism of RILT. A review on the crosstalk among signaling pathways in RILT and immunotherapy-related lung injury (IRLI) demonstrated that cell damage caused by radiotherapy contributed to the release of numerous cytokines, including IFN-c, TGF-β, and interleukin (IL)-6, which consequently induced lung injury [18]. Terefore, cytokines predictive of RILT were widely explored. Aso et al. reported that pretreatment IFN-c was overexpressed in patients with severe radiation pneumonitis (RP) [19]. Another research demonstrated that IFN-c serum levels 3 weeks after RT initiation could identify NSCLC patients predisposed to severe RP [20]. Despite the small sample size of the two studies, IFN-c could be identifed as an indicator for acute RP [18,21]. TGF-β is another classical candidate; however, some studies failed to fnd the independent predictive value of TGF-β1 for RILT, mainly because of improper sample handling, indicating it is a less practical biomarker for RILT in the clinical setting [22,23]. Other cytokines related to lung injury, such as tumor necrosis factor (TNF), interleukin (IL)-1, and IL-6, were not reliable either because some of the elevations happened only after RT [8]. Terefore, it would be preferable to determine a novel and stable biomarker indicating the risk of RILT before the initiation of RT in a larger cohort. IDO1 was broadly activated through the canonical IFN-c-IDO axis, and IDO1 can function as a signaling molecule in the regulatory circuit in response to TGF-β-driven homeostatic tolerance [24,25]. Terefore, the upregulated activity of IDO1 by proinfammatory cytokines might indicate a higher risk of developing RILT. Te Kyn : Trp ratio in serum of lung cancer patients is widely used to refect the activity of IDO1 with minimal invasiveness [14]. We measured the baseline and dynamic levels of Kyn and Trp in CRT-received NSCLC patients to explore the association between IDO1 activity and RILT. We also performed bioinformatic analyses to elucidate how IDO1 participated in the phase of RILT development.

Study Population and Treatment.
Eligible subjects include patients pathologically diagnosed with unresectable stage III NSCLC as per the American Joint Committee on Cancer (AJCC) 8th edition cancer staging manual between January 2013 and December 2017 at our institution. All patients underwent radiotherapy with or without concurrent or sequential chemotherapy. Radiation was delivered using intensity-modulated radiotherapy (IMRT), with 6-MV Xray implemented. Te median total dose is 60 Gy (28-67 Gy) in 30  fractions. Te chemotherapy regimen mainly consisted of etoposide/cisplatin and paclitaxel/carboplatin. Te study was approved by the institutional review board of the National Cancer Center, Chinese Academy of Medical Sciences, and Peking Union Medical College (IRB No. NCC-000302). All patients provided written informed consent before therapy.

Toxicity Evaluation.
RILT, including radiation pneumonitis and clinical fbrosis, is a diagnosis of exclusion. Chest computed tomography (CT) manifestations, physical examination, and clinical symptoms were taken into account when evaluating and grading RILT according to the  Te LC-MS/MS was performed on high-performance liquid chromatography coupled to a tandem mass spectrometry system (QTRAP 6500, AB SCIEX, USA) with an electrospray ionization (ESI) source and controlled by the Analyst 1.6.1 Software. Te chromatographic separation was achieved on a reversed-phase Waters HSS T3 column (2.1 × 100 mm, 1.8 μm), and the column temperature was maintained at 35°C. It was composed of water containing 0.1% formic acid (A) and 100% acetonitrile (B) using an elution gradient. Te fow rate is 250 μL/min. Data were acquired in the positive ion mode of the multiple reaction monitoring (MRM) scans. Raw data were frst processed with Multiquant 2.2 software (AB SCIEX, USA) and then calibrated using the Norm ISWSVR program in Python 3.6.

Follow-up and Statistical Analyses.
Te median followup time was 63.0 months. Patients were evaluated weekly during RT, one month after RT, and then every 3 months for 2 years and every 6 months for another 3 years. Blood tests, chest and abdomen CT scans (enhanced required if without contradictions), bone scans, and brain magnetic resonance imaging (MRI) were routinely performed during the followup. Patients and treatment characteristics, including age, gender, Eastern Cooperative Oncology Group Performance Status Scale (ECOG-PS), smoking status, pulmonary function tests (PETs), histology, clinical stage, tumor location, dose-volume parameters such as mean lung dose (MLD) and the percentage of lung volume minus gross tumor volume receiving over 5 Gy (V5) or over 20 Gy (V20), were retrieved in the electronic medical record. Te primary endpoint was G3 + RILT. Mann-Whitney U test, Kruskal-Wallis test, paired T-test, and Friedman's test were adopted for general data comparison between unpaired or paired groups. Te area under the curve (AUC) determined by receiver operating characteristic (ROC) analysis was employed to evaluate the predictive ability of covariates for G3 + RILT. Logistic regression models were used for univariate and multivariate analyses to identify the risk factor (s) of G3 + RILT, and median values were chosen to be the cutof points for all continuous variables. RNAsequencing expression profles and corresponding clinical information for NSCLC were downloaded from the TCGA dataset (https://portal.gdc.com). R software GSVA package was used to analyze, choosing parameter as method-� "ssgsea" [26]. Te correlation between gene and pathway scores was analyzed by Spearman correlation. All analysis methods and R packages were implemented by R version 4.0.3. All P values are two-sided, and P < 0.05 was considered to indicate statistical signifcance. Table 1, 113 NSCLC patients with qualifed plasma samples were enrolled in the study. Of these, 96 (85.0%) received pulmonary function tests (PETs), and 111 (98.2%) had complete dosimetric parameters retrieved. Te median age of the

Correlation between IDO Activity and RILT. Te median
Kyn : Trp ratio of the whole group was 0.07 before radiotherapy. Kyn : Trp ratio indicates the level of IDO activity as previously described. Te median preRT Kyn : Trp ratio was 0.09 in patients with G3 + RILT, which was signifcantly higher than in the non-G3 + population (0.09 vs. 0.06, P � 0.029, Figure 1). Te analyses of risk factors for G3 + RILT are shown in Table 2. Continuous covariates including forced expiratory volume in the frst second (FEV1), forced vital capacity (FVC), difusing capacity for carbon monoxide (DLCO), V5, V20, MLD, Trp, Kyn, and Kyn : Trp ratio were dichotomized using the median value as the cutof point. Tree risk factors with a P value less than 0.1 were identifed in the univariate analysis and then included in the multivariate analysis. Te result showed that the preRT Kyn : Trp ratio was signifcantly correlated with the rate of G3 + RILT (OR: 10.21; 95% confdence interval [CI]: 1.20-87.30; P � 0.034). High baseline FEV1 tended to be a protective factor for lung toxicity, although no signifcance was noted (OR: 0.21; 95% CI: 0.40-1.13; P � 0.070).
Ten ROC analysis was performed on 96 patients to explore the combined predictive value of IDO activity and PETs parameters for G3 + RILT. Tree ROC curves are shown in Figure 2. Te combination of IDO activity and FEV1 displayed the best predictive ability (AUC � 0.83, P < 0.001), as compared with IDO and FVC (AUC � 0.79, P � 0.002), or IDO activity alone (AUC � 0.68, P � 0.058). By using ROC analysis, the optimal cutof points for FEV1 and IDO activity were calculated as 59.4% and 0.069, respectively. Te incidence of G3 + RILT was 2.6% (1/38) in patients with an IDO activity ≤0.069 and FEV1 > 59.4%, and 50.0% (6/12) in those with an IDO activity >0.069 and FEV1 ≤ 59.4%.

Dynamics of IDO Activity.
IDO activity was dynamically monitored in 23 patients during RT. Te median Kyn : Trp ratio ( * 100) was 6.22 before RT, 7.02 at four weeks after RT, and 4.86 after RT, respectively. According to the Friedman test, the IDO activity was not signifcantly diferent among the three time points (P � 0.07). Paired comparisons are shown in Figure 3. IDO levels descended prominently at the end of RT as compared to mid-RT levels (P � 0.021) but remained relatively stable in the frst four weeks of RT.

Correlations between IDO1 and Six Pathways.
To explore how IDO1 took part in the development of RILT, we conducted a correlation analysis between IDO1 and six common gene pathways involved in pulmonary fbrosis and infammation based on the TCGA database. Te six pathways related to genes were involved in extracellular matrix (ECM), collagen formation, degradation of ECM, TGF-β, tumor infammation, and infammatory response. As it is shown in Figure 4, IDO1 expression was signifcantly correlated with the infammatory response in NSCLC patients (Spearman correlation score � 0.67, 95% CI: 0.63-0.70, P � 1.78e-131), while the correlation scores of the other fve pathways were too low to indicate any correlation. By the fact that all severe RILT in our cohort occurred within six months from the start of RT, during which the acute or early phase of RILT usually happened, we assume that IDO1 was primarily correlated with infammatory response rather than fbrosis [27].

Discussion
Data from our study demonstrate that the combination of pre-RT IDO activity and FEV1 can be used to construct a predictive model for severe RILT. To our knowledge, this is the frst study in the literature that associates this novel metabolomics biomarker with radiation-induced toxicity in lung cancer patients. We also use a bioinformatic tool to establish a correlation between IDO1 and acute infammatory response and thus enlighten thinking in the usage of IDO inhibitors to alleviate RILT. More importantly, both IDO1 activity and FEV1 were obtained relatively easily before the initiation of radiation, indicating that the model can serve as a promising and convenient tool for prescribing individualized RT plans in clinical practice. IDO1 could be used as a blood biomarker for G3 + RILT. Te rationale might be that IDO1 was primarily induced by IFN-c and served as a responder to TGF-β, both of which were involved in inducing lung injury and predictive of RILT. Terefore, high levels of pre-RT IDO1 might predispose patients to acute RP. Tis hypothesis was per the analysis results from the TCGA database. It is worth noting that even though we tracked 23 patients dynamically and  Journal of Oncology observed no signifcant variation in IDO1 activity during RT, we could not assess whether the levels of IDO activity at mid-RT or post-RT were predictive of RILT due to the small sample size. Further research is needed to validate our results in a larger population, and the internal mechanisms remain to be explored. Our study might enlighten a more extensive usage of IDO1 inhibitors to reduce radiation-induced toxicity in the future. Much attention of IDO1 in RT was its role as a targetable immune mediator, without mentioning toxicity. Research has shown that IDO1 levels were infuenced heterogeneously under diferent RT schemes due to the extent of immune activation [28,29]. A study reported that IDO1 blockage could overcome radiation-induced "Rebound Immune Suppression" in the tumor microenvironment and sensitized Lewis lung carcinoma (LLC) tumors to hypo-fractionated RT [30]. Another study using the LLC model also revealed that the combination of IDO inhibitor 1-methyltryptophan (1-MT) and 10 Gy RT therapy was more efective than either treatment alone [31]. Intriguingly, Chen et al. found out that IDO1 blockade could protect the normal small intestinal epithelium from radiation toxicity in preclinical models [17]. Even though the relevant mechanism was unclear, the study shed light on related explorations, and it is promising to develop a more extensive usage of IDO1 inhibitors to increase efcacy and simultaneously decrease radiation-related toxicity in the future.  Te consensus on whether PETs parameters were predictive of RILT has not been reached yet. Wang et al. [11] reported poor baseline pulmonary function did not increase the risk of symptomatic RILT in 260 NSCLC patients treated with CRT. On the contrary, Zhou et al. [32] concluded that a combination of DLCO% and MLD could predict the risk  Figure 4: Te correlation between IDO1 and pathway score was analyzed with Spearman. Te abscissa represents the distribution of the gene expression, and the ordinate represents the distribution of the pathway score. Te density curve on the right represents the trend in the distribution of pathway immune score, the upper density curve represents the trend in the distribution of the gene expression. Te value on the top represents the correlation P value, correlation coefcient, and correlation calculation method. Six pathways are included: (a) ECMrelated genes; (b) tumor infammation signature; (c) collagen formation; (d) degradation of ECM; (e) infammatory response; (f ) TGFB.
for severe RP among patients with pretreatment moderate pulmonary dysfunction. A multicenter study demonstrated that FEV1, DLCO, and FeNO before CRT predict the development of G2 + RP [33]. Our study also showed that the addition of FEV1 could signifcantly increase the model's predictive ability for G3 + RILT. Besides, PETs are widely used in clinical practice with easily accessible data, so it is convenient to include PETs parameters in predictive models.
Our study has several limitations. Firstly, this study was performed in a single center, and only a small proportion of the participants' plasma was longitudinally followed. Tese results require further validation in a larger population among multiple centers. Secondly, this study only analyzed clinical characteristics, dosimetric factors, pulmonary function parameters, and metabolic data. A more comprehensive model of RILT incorporating genetic profles and radiomics features warrants to be developed. Finally, since no patients in our cohort ever received immunotherapy, whether IDO1 activity could display similar predictive ability after consolidated immunotherapy is still unknown.
In conclusion, this study demonstrated that high baseline IDO1 activity combined with unfavorable baseline PETs was predictive of severe RILT in unresectable stage III NSCLC patients. IDO might mainly function in the early infammatory phase of RILT development instead of the late fbrosis process. Finding efective interventions to alleviate RILT using IDO inhibitors is warranted in the future.

Data Availability
Te data presented in this study are openly available at https://www.ebi.ac.uk/metabolights/MTBLS5267, with the accession number MTBLS5267.

Disclosure
Linfang Wu and Yibo Gao contributed equally as the frst author.

Conflicts of Interest
Te authors declare that they have no conficts of interest.